So multiple myeloma has a particular feature. It's called interclonal heterogeneity, and it relates to the gene expression profile in multiple myeloma, what is intra clonal heterogeneity of multiple myeloma? And how does gene expression profiling in multiple myeloma help to select the best therapy and also determine the prognostic factors? Yeah, so let me define first, the interclonal heterogeneity. We believe that is at the crux of almost all cancer. And what it simply means is that as any cancer cells in our careers myeloma cells, as it grows, it changes. And it acquires new nutritional changes, new genetic and genomic changes. So from one cell, when it becomes 2, 4, 8, and more, those newer cells have gained something that is more than what the original cell has. Some of it happens automatically without any having significant impact. Dr. Nikhil Munshi, MD.: But lot of it because of the cell selection happens to make the tumor cells become more aggressive. They become drug resistant, they become faster proliferating. And so when we look at the tumor cells when we take the bone marrow and look at myeloma cells, 100 myeloma cells. There is a lot of things common between all the cells, but there are a lot of minor differences that has been acquired over time. And so it isn't a heterogeneous population, not one single cell, mimicking all the other cells or clonal heterogeneity. As I said, it is important because this intra clonal heterogeneity provides the cancer cell ability To become resistant to treatment, that's number one. And number two, they grow faster. And in solid tumor, they also predispose the tumor cells to then metastasize in myeloma is in all the bone marrow. So we don't have that big concern. They became become extramedullary. Rarely, but in solid tumor, it can metastasize. So this interclonal heterogeneity is a bad thing. That's what our one of our problem is. Now, how can we detect intracranial heterogeneity? One simple way, is what we get what you asked about transcriptomic analysis, look at the gene expression profile, because when the tumor cells are different, each one of them are slight difference in what genes they express or not. So that's one way. And we utilize it for various purposes, I'll tell you in a second. The second way that we are now focusing even more is to look at the DNA level, because each cell may have a slightly different mutational spectrum. And that can tell us which cell was the original cell, which are the daughter cells and the granddaughter cells and etc. And we can look at the whole heterogenous population, we can what we could call a develop sort of a family tree of the cancer, in particular person that tells us what is the main cell we need to target? And then whatever else is developing from that. So both transcriptome and genome sequencing are playing an important role. Now, how does it play a role, because doing such analysis helps us identify what has the tumor cells acquired, that makes them bad cells, makes them more aggressive cell. So now looking at tumor cell, and looking at what gene mutations we observe, I could be able to predict that this person's myeloma is going to be more aggressive, and we should treat it accordingly. Similarly, when we look at the expression profile gene expression profile, depending upon what genes are expressed, or overexpressed, we can then decide this is a bad sign, more progressive sign, this is more slow growing tumor. So one thing it tells us the aggressiveness of the disease, the prognostication, and then knowing which genes are up and down, or have changed. We can then select drugs to more specifically target that particular gene to kill myeloma cells are controlling better. And so this is how we utilize this technology for possible therapeutic purpose.